Employing traditional machine learning algorithms for big data streams analysis: The case of object trajectory prediction

Journal of Systems and Software

Volumn 127, Issue , 2017, Pages 249-257

  Valsamis, Angelos ^a   Tserpes, Konstantinos ^b   Zissis, Dimitrios ^c   Anagnostopoulos, Dimosthenis ^b   Varvarigou, Theodora ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^b HAROKOPIO UNIVERSITY   (Greece)

^c UNIVERSITY OF THE AEGEAN   (Greece)

Author keywords

Data streams; Machine learning; Real time query response; Trajectory prediction

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIG DATA; DATA COMMUNICATION SYSTEMS; LEARNING SYSTEMS; SERVICE VESSELS; TRAJECTORIES;

DATA STREAM; KINEMATIC EQUATIONS; OBJECT TRAJECTORIES; QUERY RESPONSE; REAL TIME CONSTRAINTS; RESOURCE USAGE; RESOURCE UTILIZATIONS; TRAJECTORY PREDICTION;

LEARNING ALGORITHMS;

EID: 85008336840     PISSN: 01641212     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jss.2016.06.016     Document Type: Article

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